It is to be appreciated that any discussion of documents, devices, acts or knowledge in this specification is included to explain the context of the present invention. Further, the discussion throughout this specification comes about due to the realisation of the inventor and/or the identification of certain related art problems by the inventor. Moreover, any discussion of material such as documents, devices, acts or knowledge in this specification is included to explain the context of the invention in terms of the inventor's knowledge and experience and, accordingly, any such discussion should not be taken as an admission that any of the material forms part of the prior art base or the common general knowledge in the relevant art in Australia, or elsewhere, on or before the priority date of the disclosure and claims herein.
It will also be appreciated that references herein to ‘motion’ are interchangeable with ‘flow’ or ‘velocity’ (being a function of motion over time).
Cardiovascular disease is a major killer worldwide and diseases of the cardiovascular system such as thrombus formation and pulmonary diseases such as emphysema are leading causes of mortality and morbidity in developed countries. Accordingly, there is a substantial patient population that is in need of cardiac imaging so that appropriate medical therapy management can be instituted. Medical diagnosis is significantly based on echocardiograph (ECG) measurements but these have limited diagnostic value for many medical conditions and the quality can be poor.
Being able to obtain more meaningful measurements and to visually study the mechanically dynamic aspects of the cardiovascular systems would contribute to better understanding of the fundamental operation of the human body and would be a useful aid to the combat of dysfunction and disease.
The ability to recognise and treat disease or dysfunction in the cardiovascular system is dictated by our ability to image the heart and blood vessels with high resolution. In particular, it is important to detect cardiovascular problems before they become clinically evident. The earlier these problems are detected, the better the prognosis. One of the most significant problems associated with measurement of the cardiovascular system is that the constant motion of the heart makes it difficult to visualize the heart and coronary arteries sufficiently to allow full evaluation.
The ability to measure three-dimensional (3D) blood flow fields in vivo is an important capability for studying the effects of blood flow properties on the development, diagnosis and treatment of cardiovascular diseases, such as atherosclerosis. To gain useful information from in vivo blood flow field measurements, non-invasive measurement through optically opaque tissue at high resolution is required.
The development of technologies underpinning in vivo measurements of form and function of the human body are discussed in various reviews. (See for example Fouras A, Kitchen M J, Dubsky S, Lewis R A, Hooper S B and Hourigan K 2009 Journal of Applied Physics Vol. 105).
Various forms of imaging have been developed for non-invasive assessment of the function and structure of the cardiovascular system. For example, cardiovascular magnetic resonance imaging (CMR) is based on the same basic principles as magnetic resonance imaging (MRI) optimised by the use of ECG gating and rapid imaging techniques or sequences. By combining a variety of such techniques into protocols, key functional and morphological features of the cardiovascular system can be assessed.
Attempts have been made to improve cardiovascular measurement by combining of computer tomography (CT) and MRI. In essence, the very fast acquisition times of CT is used to capture images of the heart while it beats. The images are sequenced to create a movie representing the heart beating in near real time.
Compared to CT, MRI has the advantage of being able to image the heart in any plane, without the need to administer contrast material or subject a patient to radiation. However, like other currently available techniques for flow field measurement in opaque vessels, MRI based techniques, suffer from poor spatial and temporal resolution, limiting the application of these techniques for in vivo flow analysis.
Better results have been achieved with techniques such as Particle Image Velocimetry (PIV) in which the displacement of tracer particles is determined using statistical cross-correlation of regions within particle image pairs. Several variants exist for volumetric flow analysis, including Tomographic PIV, volumetric particle tracking and Holographic PIV.
PIV Imaging Generally
PIV is well known for accurate measurement of instantaneous velocity fields. PIV techniques using visible light are limited to optically transparent sample. However, the use of X-rays with PIV has extended the application of this method to opaque tissue, making this imaging mode ideal for in vivo blood flow field measurement.
In PIV, regions of fluid containing multiple tracer particles (typically illuminated by a visible wavelength laser) are imaged at two points in time, separated by a known time interval, and processed using correlation software. Specifically, the image pairs are allocated into discrete interrogation regions. Cross correlation is performed between image pairs on each interrogation region and statistically, the maximum value of the cross correlation is the most likely particle displacement within the interrogation region.
In recent years PIV has been combined with X-ray imaging. The penetrating power of X-rays allows flow to be measured within opaque objects, with applications for non-invasive, high resolution blood flow field measurements.
2D Particle Image Velocimetry
Kim and Lee (Kim G B and Lee S J 2006, Exp. Fluids 41, 195) have measured flow in tubes with particles and blood cells as tracers using X-ray PIV. The methods taught in that study are limited to two components of the velocity (averaged over the dimension perpendicular to the image plane) within the measurement volume. The PIV algorithms used belonged to the prior art relating to optical/laser based velocimetry. These algorithms assume pulsed (instantaneous) illumination and zero out-of-plane flow gradients and therefore fail to take into account the 3D characteristics of imaging real flows using X-rays. This results in a significant under estimation of flow velocity.
3D Particle Image Velocimetry
Recently X-ray PIV analysis has been extended to include 3D flow data. Fouras et al (Fouras A, Dusting J, Lewis R and Hourigan K et al, 2009 Journal of Applied Physics Vol. 102:064916) teach that the correlation peak represents a probability density function (PDF) of the velocity within the measurement volume. When combined with certain assumptions about the flow field, it is possible to convert this volumetric PDF of the velocity to a velocity profile. This results in the capability to measure 3D flow data from single projection X-ray images.
CT is a technique used to reconstruct an object in three-dimensional space from two dimensional projections. Typically, integrated object density in the projection direction is calculated from the X-ray attenuation, which will be proportional to the pixel intensity values on a digital projection image. The object structure is then reconstructed from projection images taken at different viewing angles, using Fourier back-projection or algebraic methods. Variants also exist for reconstruction of objects from few projection angles, which use iterative methods to reconstruct the sample's structure, often exploiting prior knowledge of the sample, for example that it is made up of a single material.
CTXV can thus deliver three component velocity measurements for complex 3D flow fields such as those found in the cardiovascular system. Single projection images are insufficient for evaluating three components of velocity. Images taken at a single projection angle contain no displacement information in the direction parallel to the X-ray beam. This limits single projection X-ray PIV to two component velocity measurements. In a method similar to CT, CTXV overcomes this limitation by using multiple projection angles. Signal-to-noise ratios can be enhanced using phase contrast imaging and phase retrieval methods.
Specifically, as in single projection X-ray PIV of the prior art, cross-correlation functions are calculated for interrogation regions within image pairs. The velocity field is reconstructed in axial slices, defined by the rows of interrogation regions for all projection angles. A three component, 2D, rectangular grid model represents the velocity field for each slice. Estimated cross correlation functions are generated for every angle and every interrogation region within each slice. The estimated cross-correlation functions are generated using convolution of the measured autocorrelation function with the velocity PDF for the interrogation region within the model. The velocity coefficients in the model are iteratively optimized, minimizing the error between measured cross-correlation function and the estimated cross-correlation functions, across all projection angles and interrogation regions simultaneously within that slice. Using this iterative approach, a model is reached which accurately represents the three component velocity field within each slice.
A relatively small number of projections are required and this is important for minimising radiation dosage. It also allows the integration of CTXV with a CT reconstruction such as described above, delivering simultaneous measurement of both form and function.
In particular, International patent application PCT/AU2010/001199 (claiming priority from Australian provisional 2009904481) relates to a very high resolution method and device for CTXV imaging of the movement of living tissue. CTXV has the advantage of offering the best resolution and penetration of all medical imaging modalities, with reduced delivery of X-rays compared to alternative techniques such as high resolution CT. However, any patient exposure to X-rays is a concern and there is an ongoing need to extract as much useful data as possible per exposure to X-rays or more preferably, reduced the amount of X-ray exposure without reducing the quality of data obtained.
In 2011 another medical imaging modality was established with release of the first commercial device for electrical impedance tomography (EIT). EIT creates an image of the relevant part of the body based on conductivity or permittivity from surface electrical measurements. Typically, conducting electrodes are attached to the skin of the patient and small alternating currents are applied to some or all of the electrodes. The resulting electrical potentials are measured, and the process is repeated using various applied currents. However, proposed applications of EIT have not extended past monitoring of lung function, detection of cancer in the skin and breast and location of epileptic foci in the brain.
Another imaging modality in development is hyperpolarized helium MRI (HHMRI). A patient inhales the hyperpolarized gas and MRI is used to show how the gas flows in the lung, and detect whether regions are ventilating normally or abnormally. HHMRI uses a special technique based on alignment of the nuclear magnetic moments of atoms of helium gas so that MRI signals are enhanced by up to six orders of magnitude. Imaging the lung or other areas where the water content was low, conventional MRI had proved inadequate. The hyperpolarized effect is short lived, with the effect decreasing over a period of about 80 hours depending on how the gas is stored and transported. In the past, MRI imaging has often proved inadequate in areas where water content is relatively low, such as the lung, however its application is substantially limited to areas of the body which can be permeated by helium gas.
There is also a need to increase capabilities for measuring both form and function of the heart and other tissue in the vicinity of the lungs in terms of structure, volume and motion and provide a truer 3D reconstruction of flow fields.